Evidence map›Paper›PMID 41194941›Full record

ArticleFrontiers in robotics and AI2025

Towards autonomous robot-assisted transcatheter heart valve implantation: in vivo teleoperation and phantom validation of AI-guided positioning.

Jonas Smits, Pierre Schegg, Loic Wauters, Luc Perard, Corentin Languepin, Davide Recchia, Vera Damerjian Pieters, Stéphane Lopez, Didier Tchetche, Kendra Grubb and 3 more

Abstract read
In one paragraph

Article in Frontiers in robotics and AI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Jonas Smits *Caranx Medical, Nice, France.
Pierre Schegg *Caranx Medical, Nice, France.
Loic WautersCaranx Medical, Nice, France.
Luc PerardCaranx Medical, Nice, France.
Corentin LanguepinCaranx Medical, Nice, France.
Davide RecchiaCaranx Medical, Nice, France.
Vera Damerjian PietersCaranx Medical, Nice, France.
Stéphane LopezDepartment of Cardiac Surgery, Heart Institute Arnault Tzanck, Saint Laurent du Var, France.
Didier TchetcheGroupe Cardiovasculaire Interventionnel, Clinique Pasteur, Toulouse, France.
Kendra GrubbDivision of Cardiothoracic Surgery, Emory University, Atlanta, GA, United States.
Jorgen HansenCaranx Medical, Nice, France.
Eric SejorCaranx Medical, Nice, France.
Pierre Berthet-RayneCaranx Medical, Nice, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcatheter Aortic Valve Implantation (TAVI) is a minimally invasive procedure in which a transcatheter heart valve (THV) is implanted within the patient's diseased native aortic valve. The procedure is increasingly chosen even for intermediate-risk and younger patients, as it combines complication rates comparable to open-heart surgery with the advantage of being far less invasive. Despite its benefits, challenges remain in achieving accurate and repeatable valve positioning, with inaccuracies potentially leading to complications such as THV migration, coronary obstruction, and conduction disturbances (CD). The latter often requires a permanent pacemaker implantation as a costly and life-changing mitigation. Robotic assistance may offer solutions, enhancing precision, standardization, and reducing radiation exposure for clinicians. This article introduces a novel solution for robot-assisted TAVI, addressing the growing need for skilled clinicians and improving procedural outcomes. We present an

Indexed as

AIautonomyimage-guided interventionsinterventional cardiologymedical image processingmedical roboticsrobot-assisted surgeryTAVI

Identifiers

PMID41194941
PMCPMC12583050

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.